Resize - version 10#

This page documents version 10 of operator Resize. See Resize for the latest version (since version 19).

  • Domain: ai.onnx

  • Since version: 10

Resize the input tensor. Each dimension value of the output tensor is:

output_dimension = floor(input_dimension * scale).

Inputs

  • X (T): N-D tensor

  • scales (tensor(float)): The scale array along each dimension. It takes value greater than 0. If it’s less than 1, it’s sampling down, otherwise, it’s upsampling. The number of elements of ‘scales’ should be the same as the rank of input ‘X’.

Outputs

  • Y (T): N-D tensor after resizing

Attributes

  • mode (string): Two interpolation modes: nearest (default), and linear (including bilinear, trilinear, etc)

Type Constraints

  • T: Constrain input ‘X’ and output ‘Y’ to all tensor types. Allowed types: tensor(bool), tensor(complex128), tensor(complex64), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8).